(1) Field of the Invention
The present invention relates to a waveform equalizer using a neural network, and a system for supervising and controlling the equalizer.
In the field of data communications, signals suffer distortion in their waveforms during transmission thereof, and highly precise equalization of the signals is required when the signals are received to prevent an error. The distortion is often non-linear. In addition, in particular, in the field of radio communications and mobile communications, the distortion may vary time-dependently. Since the Baud rate in recent data communication is increasing, a very high speed response is required to eliminate the distortion. Thus, a waveform equalizer is required to adaptively respond to time-dependently varying distortion including non-linear distortion in a waveform of a received signal with very high speed, to realize a highly precise equalization of the signal.
(2) Description of the Related Art
FIG. 1 shows a typical construction of a transversal type adaptive filter which is conventionally used for equalizing waveforms of received signals. The transversal type adaptive filter comprises: a tapped delay line holding a time series of data which is sampled from a received signal which is to be equalized; adaptive multipliers which multiply the time series of data by respective weight coefficients; and an adder which calculates a sum of the outputs of the multipliers. The weight coefficients are adaptively determined to realize an equalization of the received signal. However, the waveform equalizer using the transversal type adaptive filter cannot eliminate the non-linear distortion in the received signal.